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Generate vector embeddings for your data using AWS Lambda as a processor for Amazon OpenSearch Ingestion
- Amazon OpenSearch Ingestion now offers AWS Lambda support for processors that enrich and transform log, metric, and trace data in the pipeline.
- With Lambda processors, you can batch events for a single payload before invoking Lambda to optimize the pipeline for performance and cost.
- This enables you to run code without managing servers, integrating events, or maintaining runtimes.
- Integrating OpenSearch Ingestion, Lambda, and OpenSearch Serverless creates a fully serverless pipeline for embedding generation and search.
- You can easily generate embeddings by using OpenSearch's Lambda processor to dynamically generate them.
- The Lambda function invokes Amazon Bedrock's text embeddings model, enabling efficient and scalable embedding creation.
- This serverless approach allows you to focus on developing search and analytics solutions rather than managing infrastructure.
- The Lambda function receives data from OpenSearch Ingestion, invokes Amazon Bedrock to generate an embedding, and adds it to the source record.
- Using Lambda processors to enrich and transform data provides flexibility and the ability to customize event data to meet your needs.
- Amazon OpenSearch Ingestion gives you the option of using Lambda functions as processors along with built-in native processors when transforming data.
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